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Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in fermionic systems the projection needs to be carried out while imposing anti-symmetric constraints,…

Computational Physics · Physics 2025-01-08 Kousuke Nakano , Sandro Sorella , Dario Alfè , Andrea Zen

The auxiliary-field quantum Monte Carlo (AFQMC) method is a general numerical method for correlated many-electron systems, which is being increasingly applied in lattice models, atoms, molecules, and solids. Here we introduce the theory and…

Computational Physics · Physics 2021-02-24 Hao Shi , Shiwei Zhang

Quantum Monte Carlo is an efficient technique for finding the ground-state energy and related properties of small molecules. A major challenge remains in accurate determination of a molecule's geometry, i.e. the optimal location of its…

Computational Physics · Physics 2017-04-12 Jan Vrbik

The effectiveness of the recently developed Fixed-Node Quantum Monte Carlo method for lattice fermions, developed by van Leeuwen and co-workers, is tested by applying it to the 1D Kondo lattice, an example of a one-dimensional model with a…

Condensed Matter · Physics 2007-05-23 H. J. M. van Bemmel , W. van Saarloos , D. F. B. ten Haaf

Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem,…

Quantum Physics · Physics 2023-08-09 Xiaosi Xu , Ying Li

Quantum Monte Carlo methods are powerful numerical tools to accurately solve the Schr\"odinger equation for nuclear systems, a necessary step to describe the structure and reactions of nuclei and nucleonic matter starting from realistic…

Nuclear Theory · Physics 2020-05-01 Stefano Gandolfi , Diego Lonardoni , Alessandro Lovato , Maria Piarulli

We develop a time-dependent variational Monte Carlo (t-VMC) method for quantum dynamics of strongly correlated electrons. The t-VMC method has been recently applied to bosonic systems and quantum spin systems. Here, we propose a…

Strongly Correlated Electrons · Physics 2015-12-22 Kota Ido , Takahiro Ohgoe , Masatoshi Imada

The interaction and exchange-correlation contributions to the ground-state energy of an arbitrary many-electron system can be obtained from a spherical average of the wavevector-dependent diagonal structure factor (SF). We model the…

Materials Science · Physics 2015-06-25 R. Gaudoin , J. M. Pitarke

Nuclear many-body systems, ranging from nuclei to neutron stars, are some of the most interesting physical phenomena in our universe, and Quantum Monte Carlo (QMC) approaches are among the most accurate many-body methods currently available…

Nuclear Theory · Physics 2025-01-03 Ryan Curry , Rahul Somasundaram , Stefano Gandolfi , Alexandros Gezerlis , Ingo Tews

We explore different ways of incorporating accurate trial wave functions into free projection auxiliary field quantum Monte Carlo (fp-AFQMC). Trial states employed include coupled cluster singles and doubles, multi-Slater, and symmetry…

Chemical Physics · Physics 2021-04-15 Ankit Mahajan , Sandeep Sharma

Sign problem in quantum Monte Carlo (QMC) simulation appears to be an extremely hard yet interesting problem. In this article, we present a pedagogical overview on the origin of the sign problem in various quantum Monte Carlo simulation…

Strongly Correlated Electrons · Physics 2023-10-27 Gaopei Pan , Zi Yang Meng

Simulating nonadiabatic effects with many-body wave function approaches is an open field with many challenges. Recent interest has been driven by new algorithmic developments and improved theoretical understanding of properties unique to…

Chemical Physics · Physics 2016-07-12 Norm Tubman , Yubo Yang , Sharon Hammes-Schiffer , David Ceperley

Ab-initio quantum Monte Carlo (QMC) methods are a state-of-the-art computational approach to obtaining highly accurate many-body wave functions. Although QMC methods are widely used in physics and chemistry to compute ground-state energies,…

Chemical Physics · Physics 2022-01-21 Kousuke Nakano , Abhishek Raghav , Sandro Sorella

Variational quantum calculations have borrowed many tools and algorithms from the machine learning community in the recent years. Leveraging great expressive power and efficient gradient-based optimization, researchers have shown that trial…

Disordered Systems and Neural Networks · Physics 2024-08-19 Matija Medvidović , Javier Robledo Moreno

We investigate how the fixed-node diffusion Monte Carlo energy of solids depends on single-particle orbitals used in Slater--Jastrow wave functions. We demonstrate that the dependence can be significant, in particular in the case of 3d…

Materials Science · Physics 2010-09-09 Jindrich Kolorenc , Shuming Hu , Lubos Mitas

We report the first successful application of the {\it ab initio} quantum Monte Carlo (QMC) framework to a phonon dispersion calculation. A full phonon dispersion of diamond is successfully calculated at the variational Monte Carlo (VMC)…

Materials Science · Physics 2021-04-14 Kousuke Nakano , Tommaso Morresi , Michele Casula , Ryo Maezono , Sandro Sorella

We propose a new quantum Monte Carlo algorithm to compute fermion ground-state properties. The ground state is projected from an initial wavefunction by a branching random walk in an over-complete basis space of Slater determinants. By…

Condensed Matter · Physics 2016-08-31 Shiwei Zhang , J. Carlson , J. E. Gubernatis

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available…

Condensed Matter · Physics 2009-10-31 W. M. C. Foulkes , Randolph Q. Hood , R. J. Needs

High-order perturbative $\textit{ab initio}$ calculations are challenging due to the rapidly growing configuration space and the difficulty of assessing convergence. In this letter, we introduce perturbation theory quantum Monte Carlo…

Nuclear Theory · Physics 2026-05-06 Xin Zhen , Rongzhe Hu , Junchen Pei , Furong Xu

We study signal processing tasks in which the signal is mapped via some generalized time-frequency transform to a higher dimensional time-frequency space, processed there, and synthesized to an output signal. We show how to approximate such…

Numerical Analysis · Mathematics 2021-09-07 Ron Levie , Haim Avron , Gitta Kutyniok